دورية أكاديمية
Pseudotargeted metabolomics-based random forest model for tracking plant species from herbal products.
العنوان: | Pseudotargeted metabolomics-based random forest model for tracking plant species from herbal products. |
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المؤلفون: | Cai WL; State Key Laboratory of Natural Medicines, Department of Chinese Medicines Analysis, China Pharmaceutical University, No. 24 Tongjia Lane, Nanjing, China., Fang C; State Key Laboratory of Natural Medicines, Department of Chinese Medicines Analysis, China Pharmaceutical University, No. 24 Tongjia Lane, Nanjing, China., Liu LF; State Key Laboratory of Natural Medicines, Department of Chinese Medicines Analysis, China Pharmaceutical University, No. 24 Tongjia Lane, Nanjing, China., Sun FY; State Key Laboratory of Natural Medicines, Department of Chinese Medicines Analysis, China Pharmaceutical University, No. 24 Tongjia Lane, Nanjing, China., Xin GZ; State Key Laboratory of Natural Medicines, Department of Chinese Medicines Analysis, China Pharmaceutical University, No. 24 Tongjia Lane, Nanjing, China. Electronic address: xinguizhong1984@126.com., Zheng JY; State Key Laboratory of Natural Medicines, Department of Chinese Medicines Analysis, China Pharmaceutical University, No. 24 Tongjia Lane, Nanjing, China. Electronic address: zhengjy_cpu@163.com. |
المصدر: | Phytomedicine : international journal of phytotherapy and phytopharmacology [Phytomedicine] 2023 Sep; Vol. 118, pp. 154927. Date of Electronic Publication: 2023 Jun 08. |
نوع المنشور: | Journal Article |
اللغة: | English |
بيانات الدورية: | Publisher: Urban & Fischer Verlag Country of Publication: Germany NLM ID: 9438794 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1618-095X (Electronic) Linking ISSN: 09447113 NLM ISO Abbreviation: Phytomedicine Subsets: MEDLINE |
أسماء مطبوعة: | Publication: Stuttgart : Urban & Fischer Verlag Original Publication: Stuttgart ; New York : G. Fischer, c1994- |
مواضيع طبية MeSH: | Drugs, Chinese Herbal*/pharmacology , Astragalus Plant* , Saponins*/pharmacology, Astragalus propinquus ; Random Forest ; Flavonoids |
مستخلص: | Background: The "one-to-multiple" phenomenon is prevalent in medicinal herbs. Accurate species identification is critical to ensure the safety and efficacy of herbal products but is extremely challenging due to their complex matrices and diverse compositions. Purpose: This study aimed to identify the determinable chemicalome of herbs and develop a reasonable strategy to track their relevant species from herbal products. Methods: Take Astragali Radix-the typical "one to multiple" herb, as a case. An in-house database-driven identification of the potentially bioactive chemicalome (saponins and flavonoids) in AR was performed. Furthermore, a pseudotargeted metabolomics method was first developed and validated to obtain high-quality semi-quantitative data. Then based on the data matrix, the random forest algorithm was trained to predict Astragali Radix species from commercial products. Results: The pseudotargeted metabolomics method was first developed and validated to obtain high-quality semi-quantitative data (including 56 saponins and 49 flavonoids) from 26 batches of AR. Then the random forest algorithm was well-trained by importing the valid data matrix and showed high performance in predicting Astragalus species from ten commercial products. Conclusion: This strategy could learn species-special combination features for accurate herbal species tracing and could be expected to promote the traceability of herbal materials in herbal products, contributing to manufacturing standardization. Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. (Copyright © 2023 Elsevier GmbH. All rights reserved.) |
فهرسة مساهمة: | Keywords: Astragali Radix; Herbal products; Pseudotargeted metabolomics; Random forest model |
المشرفين على المادة: | 0 (Drugs, Chinese Herbal) 0 (Flavonoids) 0 (Saponins) |
تواريخ الأحداث: | Date Created: 20230618 Date Completed: 20230807 Latest Revision: 20230807 |
رمز التحديث: | 20231215 |
DOI: | 10.1016/j.phymed.2023.154927 |
PMID: | 37331178 |
قاعدة البيانات: | MEDLINE |
تدمد: | 1618-095X |
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DOI: | 10.1016/j.phymed.2023.154927 |